Joel Chan is an Assistant Professor in the University of Maryland’s College of Information Studies (iSchool), and Human-Computer Interaction Lab (HCIL). Previously, he was a Postdoctoral Research Fellow and Project Scientist in the Human-Computer Interaction Institute at Carnegie Mellon University. He received his Ph.D. in Cognitive Psychology at the University of Pittsburgh. His research and teaching focus on the intersection of people, information, and creativity. He wants to know how they (can best) combine to enable us to design the future(s) we want to live in.
knowledge sharing, collective/collaborative innovation, design
- SOLVENT: A
Mixed InitiativeSystem for Finding Analogies between Research Papers. Chan, Joel, Chang, Joseph Chee, Hope, Tom, Shahaf, Dafna, and Kittur, Aniket. Proceedings of ACM Human-Computer Interaction: CSCW 2018
- Comparing Different Sensemaking Approaches for Large-Scale Ideation. Chan, Joel, Dang, Steven, and Dow, Steven P. In Proceedings of the 2016 CHI Conference on Human Factors in Computing Systems 2016
- Improving Crowd Innovation with Expert Facilitation. Chan, Joel, Dang, Steven, and Dow, Steven P. In Proceedings of the 19th ACM Conference on Computer-Supported Cooperative Work & Social Computing 2016
- Do The Best Design Ideas (Really) Come From Conceptually Distant Sources Of Inspiration? Chan, Joel, Dow, Steven P., and Schunn, Christian D. Design Studies 2015